The Text-Score Allocation Model : Finding Latent Topics of Online Review Documents and Multi-Item Ratings

Katsumata, Sotaro; Kim, Seungjin

Discussion Papers In Economics And Business, 2020, 20-01, 1-35

アクセス数:287件（2025-07-11 09:37 集計）

固定URL: https://hdl.handle.net/11094/73808

論文情報

ファイル出力 EndNote Basic出力 Mendeley出力

タイトル
The Text-Score Allocation Model : Finding Latent Topics of Online Review Documents and Multi-Item Ratings
著者
NRID
1000080613588 1000080613588
ORCID
0000-0003-0496-8863 0000-0003-0496-8863
researchmap permalink
sotaro.katsumata sotaro.katsumata
Scopus Author ID
57008851200 57008851200
著者名
Katsumata, Sotaro
著者名
Kim, Seungjin
キーワード等
Topic Modeling
Customer Reviews
Forecasting
抄録
This study focuses on online review data in which comments are written in natural languages and evaluations are attached as integers. This study develops a topic model incorporating both natural languages and evaluation scores, expanding latent Dirichlet allocation (LDA). The model consists of two components: LDA and a Dirichlet-binomial clustering model. The latter assumes binomial distributions for the review scores. Since the model assumes conjugate distributions, we can apply a fast and stable estimator based on collapsed Gibbs sampling to estimate the parameters. Further,the model enables us to examine the relationship between vocabulary words and review scores based on the topic allocation results.
出版者
Graduate School of Economics, Osaka University
収録物名
Discussion Papers In Economics And Business
巻(号)
20-01
ページ
1-35
刊行年月
2020-01
言語
英語
ハンドルURL
https://hdl.handle.net/11094/73808
NCID
AA1160366X
関連情報
URI
http://www2.econ.osaka-u.ac.jp/econ_society/dp/2001.pdf
アクセス権
metadata only access
カテゴリ
ディスカッション／ワーキング・ペーパー DP/WP
Discussion Papers In Economics And Business